code: def test_dynamo(
      self, batch_size, kernel_size, device, dtype, torch_optimizer
  ):
      if (
          torch_version() in {"2.1.1"}
          and dtype == torch.float64
          and (
              isinstance(kernel_size, int)
              or kernel_size[0] == kernel_size[1]
          )
      ):
          pytest.skip(
              "Canny compiled failing into fp64 for kernel sizes where kx and ky are equals"
          )
      inpt = torch.ones(
          batch_size, 3, 10, 10, device=device, dtype=dtype
      )
      op = Canny(kernel_size=kernel_size)
      op_optimized = torch_optimizer(op)
  
      expected_magnitude, expected_edges = op(inpt)
      actual_magnitude, actual_edges = op_optimized(inpt)
  
      self.assert_close(actual_magnitude, expected_magnitude)
      self.assert_close(actual_edges, expected_edges)
  
file_path: kornia/test/filters/test_canny.py
imports: import pytest
  import torch
  from kornia.filters import Canny, canny
  from kornia.testing import BaseTester, tensor_to_gradcheck_var
  from kornia.utils._compat import torch_version
label_desc: Use image node_id 11 for calling the TestCanny obj's underlying member method code with example usage: obj.test_dynamo(batch_size, kernel_size, device, dtype, torch_optimizer) without return types